As technology and the Internet become integrated into every facet of people's lives, the way people interact with these technologies is changing. Instead of manually logging scores we wear devices to count steps, heart rate, and UV exposure; instead of taking notes, we receive automatically synthesized summaries; instead of performing a web search and sifting through results, we ask our digital personal assistant to fetch an answer to our questions. Many digital content producers, social media providers, search engine providers, cell phone providers, and operating system providers have released various automated systems for retrieving relevant data, whether it is explicitly asked for by a user or whether a system intuitively determines that a user will find such data useful. As an example, some cell phones include automated systems that allow a user to pose a question and receive an answer in a conversational manner.
While these automated systems have attained a great deal of notoriety, this notoriety is as often a result of failures as it is from successes. Users of these systems have to deal with the occasional inability of the system to obtain answers to their questions or incorrect or even absurd results. There are a variety of reasons for these shortcomings. In some cases, the problem comes down to a lack of available data. When a user asks a question that the automated system has not seen before, it may fall back on a default operation such as a web search. In some cases, the problem arises from an inability to properly categorize available data. When a question is asked that is similar to a previously identified question, the system may not be able to correctly determine a correspondence between the questions, and thus may not correctly provide an answer. In some cases, the problem is an over-abundance of data without an ability to properly identify a context. For example, a user can ask the question “where should I go for lunch?” The system can provide any of many known answers, but some of these may not be relevant to the particular user asking the question.
The techniques introduced here may be better understood by referring to the following Detailed Description in conjunction with the accompanying drawings, in which like reference numerals indicate identical or functionally similar elements.